A Dynamic Pivoting Algorithm Based on Spatial Approximation Indexes
Abstract
Metric indexes aim at reducing the amount of distance evaluations carried out when searching a metric space. Spatial approximation trees (sa-trees for short), in particular, are efficient data structures, which have shown to be competitive in metric spaces of medium to high difficulty, or queries with low selectivity. Sa-trees can be also made dynamic, and can use the available space to improve the query performance adding pivot information. In this paper we extend previous work on dynamic sa-trees with pivots, and show how the pivot information can be used to a full extent to improve the search performance. The result is a technique that allows one to traverse a dynamic sa-tree without necessarily comparing all traversed nodes against the query object. As a result, the novel algorithm makes a much better use of the available space, yielding a saving of distance computations of about 10% to 70%, compared with previous sa-tree schemes that use pivot information.
Más información
| Título según WOS: | A Dynamic Pivoting Algorithm Based on Spatial Approximation Indexes |
| Título según SCOPUS: | A dynamic pivoting algorithm based on spatial approximation indexes |
| Título de la Revista: | GAMES AND LEARNING ALLIANCE, GALA 2024 |
| Volumen: | 8821 |
| Editorial: | SPRINGER INTERNATIONAL PUBLISHING AG |
| Fecha de publicación: | 2014 |
| Página de inicio: | 70 |
| Página final: | 81 |
| Idioma: | English |
| DOI: |
10.1007/978-3-319-11988-5_7 |
| Notas: | ISI, SCOPUS |